AI is transforming the developer experience. Embrace the change

A lot of question marks loom over the future of AI and jobs. But for today’s developers, AI-driven development can be a solution to the reality of today: Development teams are stretched thin, challenged by many competing tasks that leave little time to do what they love: developing software.

It’s not an exaggeration to say that every developer will eventually become an AI developer, but even today, 92% of US-based developers already use AI coding tools inside and outside of work. These AI tools are not fundamentally changing what developers do. But they offer improved efficiency—saving time on repetitive tasks, security checks, frequent code changes, writing tests, documentation, and more. Now, the question for engineering teams everywhere isn’t about what impact AI will have on engineering; it’s about how they can make the most of AI today.

How companies can embrace AI while putting people first

For all the promise of generative AI, people remain every organization’s most valuable asset. AI offers an opportunity to harness developers’ enthusiasm, while empowering them to introduce integral systems—without taking up significantly more time.

To do that, though, it’s vital that developers have access to the right technology. Companies are well advised to hand developers the keys to AI-powered productivity and collaboration tools, provide them with access to large language models (LLMs) from different providers, and allow them to try copilot platforms that help them generate code, create data models, and test data for applications. 

From sandboxes to hackathons, and more, there are many ways to implement AI solutions, with features that can push developers to harness the technology in novel ways that could lead to beneficial data and insights. The more leaders can do to help teams embrace AI tools easily, the better off they’ll be for it. 

Here I’ll outline three approaches that organizations should consider as their development teams explore AI. 

Embrace an open-ecosystem approach

The AI market is moving so fast that it is unlikely that every business has a true AI expert in their organization. That’s why it’s important to take a community-guided approach. By inviting industry leaders to speak with your teams, allowing them to test and explore AI tools themselves, and facilitating exchange with an online community, you’ll ensure that they are always informed about the most up-to-date content out there. 

We’ve already seen some applicable use cases for AI in the world, like using an LLM to perform company research before reaching out or creating a personalized outbound e-mail for a demand generation campaign based on LinkedIn profile content. Discovering these best-in-class efforts often requires an outside influence. If you’re betting on a course that you built three months ago and rolled out internally, you’re already far behind the market.

In the current phase of the AI era, organizations should prioritize this thoughtful, outside-in approach to ensure that their teams are getting exposed to what’s most relevant. 

Establish a framework for AI exploration

In the fast-evolving landscape of generative AI, establishing a solid foundation for targeted and compliant use is paramount. By developing a comprehensive framework that accounts for ethics, data usage, security, and more, companies can ensure that their developers are prepared to navigate the ethical challenges that arise in the AI sector. 

Organizations can build this collective understanding through short, engaging training sessions that demonstrate the power of AI and by involving experts outside of engineering to learn about new topics. With AI projects that typically span teams and departments, a framework provides a standardized process that can facilitate communication and collaboration among multiple groups—especially as companies scale their AI initiatives. This framework will ensure that AI efforts contribute to strategic priorities and clearly define success metrics and milestones. 

By ensuring there are no barriers between teams within the organization, everyone can generate ideas faster, make purchase decisions faster, and change course faster when it comes to AI. 

Make AI work fun 

Organizations shouldn’t stop at providing guidelines, though. The next most important thing companies can offer is a safe space for their developers to experiment. Doing so allows them to tap into the creativity and innovation of generative AI, encouraging them to unleash their imagination and push the boundaries of the technology. 

This feeling of “off-the-clock” exploration can foster a culture of continuous learning—without the rigidity of a structured learning program. Ultimately, it’s more important that developers feel empowered to explore, play, and build enthusiasm for AI tools than it is to enforce a “correct” way to use AI. And without the stress of business priorities, developers are more likely to take novel, innovative approaches to AI, which could pay dividends in the long run.

By providing opportunities for developers to explore and to help everyone around them understand these new tools, organizations can set their development teams up for long-term success—while leveraging the current momentum around AI.

Making the shift to AI-assisted development

Developers are finding new applications for AI every day. But perhaps more importantly, it’s becoming critical for company leadership to understand how AI is changing the way developers work and how to adopt the technology for their engineering teams. 

The more developers’ enthusiasm around AI grows, and the more capable developers get at implementing AI tools, the greater the need to establish a framework tailored to the organization and to create a safe space to explore the technology. 

By giving developers the freedom to explore AI, and license to help everyone around them understand these new tools, organizations can set their development teams up for long-term success—without giving into the hype. 

Andre Bechtold serves as the senior vice president and head of solution and innovation experience at SAP, where he provides product and solution learning and enablement opportunities for customers, partners, and employees and oversees SAP learning, training, customer demos, and the SAP Experience Centers.

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Generative AI Insights provides a venue for technology leaders—including vendors and other outside contributors—to explore and discuss the challenges and opportunities of generative artificial intelligence. The selection is wide-ranging, from technology deep dives to case studies to expert opinion, but also subjective, based on our judgment of which topics and treatments will best serve InfoWorld’s technically sophisticated audience. InfoWorld does not accept marketing collateral for publication and reserves the right to edit all contributed content. Contact doug_dineley@foundryco.com.